#HIDDEN
from IPython.display import Image
from IPython.core.display import HTML
from ipywidgets import Text, Dropdown, Output, interact
from matplotlib import pyplot as plt
from pandas import DataFrame, merge, read_csv, Series, to_datetime
import cufflinks as cf
import qgrid
cf.go_offline()
# cf.set_config_file(offline=False, world_readable=True)
cf.set_config_file(offline=True, world_readable=True)
###  nbi:hide_in

GLBRC collaboration

Adina, Ashley, Nejc, Shane¶

MetaG Sequencing and alignment Summaries
- Inputs:
  - 136 Phred-33 fastq files from samples obtained from washes of Switchgrass and Miscanthus transfered from JGI. Metadata
  - Illumina TruSeq version 3.2 sequencing adapters.
- Outputs:
MetaG Analysis
- Inputs:
  - The MAGs assembly created by concatenating bins with $>=$ 50% commpleteness
  - Functional Gene Count table, mapped to KEGG/functions using this annotation methodology. My script that follows these steps is here.
- Research Questions:
MetaT Sequencing and alignment Summaries
- Inputs:
  - 74 Switchgrass samples and their respective fastq files. Metadata
  - Illumina TruSeq version 3.2 sequencing adapters.
- Outputs:
MetaT Analysis

MetaG Sequencing and Alignment Summaries

Full mapping script

Adapter Trimming and QC (Trimmomatic) Report

What is the abundance and quality of the reads in each sample?

Step 1. Split JGI files in PE files

split-paired-reads.py --gzip -1 \$sample.fastq.pe1.gz -2 \$sample.fastq.pe2.gz \$jgi_combined_fastq

Step 2. Use trimmomatic to QC reads

trimmomatic PE -phred33 \$sample.fastq.pe1.gz \$sample.fastq.pe2.gz \$sample.fastq.pe1.gz \$sample.fastq.se1.gz \$sample.fastq.pe2.gz \$sample.fastq.se2.gz \
   ILLUMINACLIP:TruSeq3-PE-2.fa:2:30:10:8:TRUE \
   LEADING:3 \
   TRAILING:3 \
   SLIDINGWINDOW:4:15 \
   MINLEN:36

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Adapter Trimming and QC (Trimmomatic) Report
Host Plant Alignment Report
Fungal Alignments
Alignment Conclusions

#HIDDEN
# <!-- # #HIDDEN
# # tImages = {"MetaG":Image("images/TrimReport_MetaG.png"),"MetaT":Image("images/MetaT_trimmomatic_plot.png")}
# # @interact
# # def trimReport(Source=["MetaG","MetaT"]):return tImages[Source] 
# <img src="images/TrimReport_MetaG.png"></img>
# -->
HTML("html/MetaG_TrimStats.html")

MultiQC Report

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Report generated on 2019-10-27, 12:13 based on data in: /mnt/research/ShadeLab/GLBRC/mapping/metaG/fullAssembly/trimStats

Trimmomatic is a flexible read trimming tool for Illumina NGS data.

Host Plant Alignment Report

When the reads are aligned to plant reference genomes, how many of the reads are plant-aligned reads?

Step 1. Align reads to respective host reference assembly

if [[ \$sample == *"G5"* ]]; then
       SAMFILE=\$sample.SWGRASS.sam
       BAMFILE=\$sample.SWGRASS.bam
       bowtie2 --threads \$THREADS -x \$SWITCHGRASS
             -1 \$sample.fastq.pe1.gz -2 \$sample.fastq.pe2.gz
             -U \$sample.fastq.se12.gz -S \$sample.SWGRASS.sam 2>\$sample.stat
else
       SAMFILE=\$sample.MISCANTS.sam
       BAMFILE=\$sample.MISCANTS.bam
       bowtie2 --threads \$THREADS -x \$MISCANTHUS
             -1 \$sample.fastq.pe1.gz -2 \$sample.fastq.pe2.gz
             -U \$sample.fastq.se12.gz -S \$sample.MISCANTS.sam 2>\$sample.stat
fi

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Adapter Trimming and QC (Trimmomatic) Report
Host Plant Alignment Report
Fungal Alignments
Alignment Conclusions

#HIDDEN
HTML(filename="html/BothPerc.html")

Sequencing and alignment Summaries

Fungal Alignment Report

What reads are fungal reads?

Step 1. Extract reads that don't align the plant assembly

# A. Convert sam > bam
samtools view -bS \$SAMFILE > \$BAMFILE

# B. Extract all unmapped reads (-f 4) that don't have a mate mapped (-F 256 i.e. both unmapped)
samtools view -b -f 4 -F 256 \$BAMFILE > \$sample.unmapped.bam

# C. Sort the reads
samtools sort -n \$sample.unmapped.bam -o \$sample.unmapped_sorted.bam

# D. Split the unmapped reads in R1 & R2 (back into paired end)
bedtools bamtofastq -i \$sample.unmapped_sorted.bam -fq \$sample.R1.fastq -fq2 \$sample.R2.fastq

Step 2. Align the reads to the combined fungal assemblies

bowtie2 -x \$FUNGAL -1 \$sample.R1.fastq -2 \$sample.R2.fastq -S \$sample.fungal.sam 2>\$sample.fungal.stat

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Adapter Trimming and QC (Trimmomatic) Report
Host Plant Alignment Report
Fungal Alignments
Alignment Conclusions

#HIDDEN
HTML(filename='html/FungalAlign.html')

Sequencing and alignment Conclusions

Sequencing Observations

What patterns are there over the season?

The percentage of plant reads sequenced is high thoughout the season and tapers off towards the end of the season. This may be do to senescence of plant cells.
Alignment to the 6 selected fungal assemblies is low, but picks up during the warmer months. Overall, reads aligning to the combined fungal assembly were <10% of the non-plant reads.

Annotation Summary¶

The annotations were performed using KEGG's prokaryotic peptides and eukaryotic peptides

Based on the high-overlap, we decided to use the mags instead of the assembly for alignment

MetaG Analysis¶

MAG Stats¶

MAGs generated with reads that did not align to the fungal/host assemblies using metabat. Stats were then generated with checkm and the command below, results for that stats are below that. checkm lineage_wf -t 20 -x fa Final.contigs.fa.metabat-bins20 metaBinsStats

#HIDDEN
HTML(filename="html/MAG_Stats.html")

Table of the bins with ≥ 50% completeness

	Bin Id	Marker lineage	Unnamed: 2	# Genomes	# Markers	# Marker sets	0	1	2	3	4	Completeness	Contamination	Strain heterogeneity
0	bin.7	o__Burkholderiales	(UID4105)	54	553	264	3	534	16	0	0	99.66	2.65	43.75
1	bin.39	f__Enterobacteriaceae	(UID5054)	223	874	303	38	829	7	0	0	99.05	0.70	71.43
2	bin.67	o__Pseudomonadales	(UID4488)	185	812	308	35	751	26	0	0	97.79	3.53	46.15
3	bin.157	o__Actinomycetales	(UID1593)	69	400	198	21	364	14	1	0	96.84	4.73	29.41
4	bin.125	o__Actinomycetales	(UID1663)	488	310	185	18	276	16	0	0	93.96	4.23	68.75
5	bin.164	o__Burkholderiales	(UID4000)	193	427	214	44	379	4	0	0	92.27	1.64	50.00
6	bin.117	o__Rhizobiales	(UID3654)	92	481	319	66	401	14	0	0	90.51	3.00	78.57
7	bin.202	o__Cytophagales	(UID2936)	47	454	336	82	362	10	0	0	89.90	2.68	80.00
8	bin.181	o__Rhizobiales	(UID3654)	92	481	319	73	381	27	0	0	89.84	5.71	33.33
9	bin.188	o__Burkholderiales	(UID4000)	193	427	214	77	296	51	3	0	87.56	15.48	60.00
10	bin.198	o__Cytophagales	(UID2936)	47	454	336	54	379	21	0	0	87.28	3.43	61.90
11	bin.121	o__Burkholderiales	(UID4000)	193	427	214	68	339	20	0	0	87.25	5.02	30.00
12	bin.95	o__Burkholderiales	(UID4002)	107	574	251	67	493	14	0	0	87.18	2.41	78.57
13	bin.214	o__Flavobacteriales	(UID2815)	123	324	204	67	252	5	0	0	87.11	1.49	100.00
14	bin.195	k__Bacteria	(UID203)	5449	104	58	25	54	16	8	1	82.99	35.50	78.26
15	bin.105	o__Actinomycetales	(UID1593)	69	400	198	104	282	14	0	0	75.84	4.46	28.57
16	bin.88	k__Bacteria	(UID203)	5449	104	58	28	39	22	10	5	73.82	38.55	34.15
17	bin.142	c__Deltaproteobacteria	(UID3216)	83	247	155	49	194	4	0	0	73.12	2.58	25.00
18	bin.148	o__Sphingomonadales	(UID3310)	26	569	293	154	398	17	0	0	72.70	2.26	17.65
19	bin.112	o__Flavobacteriales	(UID2815)	123	324	204	100	214	10	0	0	71.14	2.71	80.00
20	bin.91	o__Sphingomonadales	(UID3310)	26	569	293	191	261	99	18	0	69.76	25.37	22.22
21	bin.206	o__Rickettsiales	(UID3809)	83	324	211	86	226	12	0	0	69.27	3.82	58.33
22	bin.93	o__Actinomycetales	(UID1802)	274	385	212	105	254	25	1	0	68.43	8.09	53.57
23	bin.114	o__Actinomycetales	(UID1663)	488	310	185	92	215	3	0	0	67.03	0.69	33.33
24	bin.104	k__Bacteria	(UID203)	5449	103	57	52	38	12	1	0	67.01	12.41	46.67
25	bin.134	o__Rhizobiales	(UID3654)	92	481	319	183	288	10	0	0	66.91	2.00	80.00
26	bin.163	o__Rickettsiales	(UID3809)	83	324	211	101	216	7	0	0	66.80	2.53	14.29
27	bin.146	o__Actinomycetales	(UID1697)	387	330	193	131	190	9	0	0	64.35	2.27	0.00
28	bin.205	o__Actinomycetales	(UID1697)	387	330	193	125	198	7	0	0	63.48	3.11	42.86
29	bin.200	k__Bacteria	(UID203)	5449	104	58	59	43	2	0	0	62.47	2.59	100.00
30	bin.57	o__Cytophagales	(UID2936)	47	454	336	192	256	6	0	0	60.73	1.79	50.00
31	bin.10	k__Bacteria	(UID203)	5449	104	58	63	41	0	0	0	60.69	0.00	0.00
32	bin.208	c__Alphaproteobacteria	(UID3305)	564	337	221	134	193	10	0	0	60.38	2.96	90.00
33	bin.2	o__Actinomycetales	(UID1815)	120	574	266	221	331	22	0	0	59.37	3.03	36.36
34	bin.175	o__Burkholderiales	(UID4000)	193	427	214	171	246	8	2	0	58.90	2.35	50.00
35	bin.116	k__Bacteria	(UID203)	5449	104	58	61	31	11	0	1	58.79	18.97	100.00
36	bin.66	o__Sphingomonadales	(UID3310)	26	569	293	263	287	17	2	0	56.39	5.49	52.17
37	bin.139	o__Actinomycetales	(UID1593)	69	400	198	165	203	31	0	1	56.31	7.46	64.86
38	bin.156	k__Bacteria	(UID203)	5449	104	58	60	39	5	0	0	56.04	6.19	100.00
39	bin.55	k__Bacteria	(UID203)	5449	103	57	65	28	9	1	0	56.01	13.16	66.67
40	bin.84	o__Burkholderiales	(UID4000)	193	427	214	212	206	9	0	0	55.53	2.95	11.11
41	bin.171	k__Bacteria	(UID203)	5449	104	58	35	31	24	14	0	55.22	22.74	3.03
42	bin.132	f__Rhizobiaceae	(UID3564)	78	840	354	352	470	18	0	0	52.64	1.16	61.11
43	bin.54	k__Bacteria	(UID203)	5449	103	57	69	34	0	0	0	52.63	0.00	0.00
44	bin.199	k__Bacteria	(UID203)	5449	104	58	65	37	2	0	0	52.47	3.45	50.00
45	bin.115	k__Bacteria	(UID203)	5449	104	58	43	38	12	11	0	52.30	19.17	66.67
46	bin.120	o__Sphingomonadales	(UID3310)	26	569	293	274	271	23	1	0	51.10	5.80	38.46
47	bin.33	k__Bacteria	(UID203)	5449	104	58	68	36	0	0	0	50.17	0.00	0.00
48	bin.65	k__Bacteria	(UID203)	5449	104	58	64	39	1	0	0	49.32	1.72	100.00

MetaT Analysis

Overarching analysis - changes in metagenome content over time

All bins with at least 50% completeness were used in a combined assembly. The analysis below comes from the counts for each sample. These counts were normalized by the number of reads that did not align to the fungal or host assemblies.

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Functional annotation accumulation over time
Is time a factor that affects the functional richness of phylosphere communities (Alpha Diversity)?
Do we see changes over time in functional richness?
Is there a difference between treatment (Fertilized vs. Unfertilized)?
Is there a difference between host plant?
PCoA of functional counts
Is there similarity between the WGS communities and the 16S data?
How variable are metagenomes across replicate time points?

COG accumulation over time

pcoa

Is time a factor that affects the functional richness of phylosphere communities (Alpha Diversity)?

Switchgrass Pearson's product-moment correlation
Data:	Time and Richness
t = 10.223	df = 62	p-value = 6.316e-15
sample estimates: cor 0.7922484

Switchgrass Pearson's product-moment correlation
Data:	Time and Shannon
t = 7.1534	df = 62	p-value = 1.166e-09
sample estimates: cor 0.6724267

Switchgrass Pearson's product-moment correlation
Data:	Time and Pielou
t = 5.6951	df = 62	p-value = 3.622e-07
sample estimates: cor 0.586056

Miscanthus Pearson's product-moment correlation
Data:	Time and Richness
t = 8.5659	df = 70	p-value = 1.658e-12
sample estimates: cor 0.7153784

Miscanthus Pearson's product-moment correlation
Data:	Time and Shannon
t = 6.1267	df = 70	p-value = 4.675e-08
sample estimates: cor 0.5908107

Miscanthus Pearson's product-moment correlation
Data:	Time and Pielou
t = 7.1602	df = 70	p-value = 6.369e-10
sample estimates: cor 0.6502079

Do we see changes over time in functional richness?

Call: adonis(formula = dist.otu ~ map_16S\$time_numeric)

Permutation: free Number of permutations: 999

Terms added sequentially (first to last)

	Df	SumsOfSqs	MeanSqs	F.Model	R2	Pr(>F)
map_16S$time_numeric	1	1.9356	1.93562	47.814	0.26298	0.001 ***
Residuals	134	5.4246	0.04048		0.73702
Total	135	7.3603			1.000000

images/Level1_Mags.png

images/Level2_Mags.png

Is there a difference between treatment (Fertilized vs. Unfertilized)?

Call: adonis(formula = dist.otu ~ map_16S\$treatment)

Permutation: free Number of permutations: 999

Terms added sequentially (first to last)

	Df	SumsOfSqs	MeanSqs	F.Model	R2	Pr(>F)
map_16S$treatment	1	0.0289	0.028930	0.52878	0.00393	0.755
Residuals	134	7.3313	0.054711		0.99607
Total	135	7.3603			1.000000

Is there a difference between host plant?

Call: adonis(formula = dist.otu ~ map_16S\$plant)

Permutation: free Number of permutations: 999

Terms added sequentially (first to last)

	Df	SumsOfSqs	MeanSqs	F.Model	R2	Pr(>F)
map_16S$plant	1	0.1617	0.161704	3.0101	0.02197	0.027 *
Residuals	134	7.1986	0.053721		0.97803
Total	135	7.3603			1.000000

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Functional annotation accumulation over time
Is time a factor that affects the functional richness of phylosphere communities (Alpha Diversity)?
Do we see changes over time in functional richness?
Is there a difference between treatment (Fertilized vs. Unfertilized)?
Is there a difference between host plant?
PCoA of functional counts
Is there similarity between the WGS communities and the 16S data?
How variable are metagenomes across replicate time points?

PCoA

Is there similarity between the WGS communities and the 16S data (mantel/procrustes)?

Mantel statistic based on Pearson's product-moment correlation Call: mantel(xdis = genes.dist, ydis = otu.dist) Mantel statistic r: 0.6526 Significance: 0.001 Upper quantiles of permutations (null model): 90% 95% 97.5% 99% 0.0833 0.1194 0.1458 0.1849 Permutation: free Number of permutations: 999 Call: protest(X = genes.pcoa, Y = otu.pcoa) Procrustes Sum of Squares (m12 squared): 0.5402 Correlation in a symmetric Procrustes rotation: 0.6781 Significance: 0.001 Permutation: free Number of permutations: 999

How variable are metagenomes across replicate time points?

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Functional annotation accumulation over time
Is time a factor that affects the functional richness of phylosphere communities (Alpha Diversity)?
Do we see changes over time in functional richness?
Is there a difference between treatment (Fertilized vs. Unfertilized)?
Is there a difference between host plant?
PCoA of functional counts
Is there similarity between the WGS communities and the 16S data?
How variable are metagenomes across replicate time points?

Metatranscriptomic Sequencing

MetaT Sequencing and Alignment Summaries

Full mapping script

What is the abundance and quality of the reads in each sample?

#HIDDEN
HTML("html/MetaT_TrimStats.html")

MultiQC Report

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Report generated on 2020-02-25, 12:44 based on data in: /mnt/research/ShadeLab/GLBRC/mapping/metaT/fullAssembly/trimStats

How do the reads align to the Switchgrass assembly?

Season Trend

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Report regenerated on 2020-02-18, 21:40 based on data in: /mnt/research/ShadeLab/GLBRC/mapping/metaT/hostRemovalFlagstats

There are 6 possible types of alignment: * PE mapped uniquely: Pair has only one occurence in the reference genome. * PE mapped discordantly uniquely: Pair has only one occurence but not in proper pair. * PE one mate mapped uniquely: One read of a pair has one occurence. * PE multimapped: Pair has multiple occurence. * PE one mate multimapped: One read of a pair has multiple occurence. * PE neither mate aligned: Pair has no occurence.

How do the reads align to the MAG assembly?

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This plot shows the number of reads aligning to the reference in different ways.
Please note that single mate alignment counts are halved to tally with pair counts properly.

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Report generated on 2020-02-25, 12:44 based on data in: /mnt/research/ShadeLab/GLBRC/mapping/metaT/fullAssembly/trimStats

Outline

Research Questions

Next Steps¶

Fix the metadata to ensure that each sample is accounted for and we have the seq files (Nejc) ✓ Completed Wednesday, Feb 19,2020. Delivered by Kiera
Modify the R analysis script to read results from the MetaT data (Nejc & Shane)

In order for this to progress, 1 had to be complete. The next step is figure out why the metadata for the MetaT is not meshing with the R script.
Explore the Kallisto output to determine how to extract annotations (Shane)

Kallisto has an arguement to export a bam file when it runs, but I do not know how these bam files work or if they are the same thing as a bam from bowtie2. I am working with kallisto to get a bam file now and then I will see if that file works to extract annotations from the contigs

Home

GLBRC collaboration

Adina, Ashley, Nejc, Shane¶

MetaG Sequencing and Alignment Summaries

Adapter Trimming and QC (Trimmomatic) Report

What is the abundance and quality of the reads in each sample?

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Host Plant Alignment Report

When the reads are aligned to plant reference genomes, how many of the reads are plant-aligned reads?

Sequencing and alignment Summaries

Fungal Alignment Report

What reads are fungal reads?

Sequencing and alignment Conclusions

Sequencing Observations

What patterns are there over the season?

Annotation Summary¶

MetaG Analysis¶

MAG Stats¶

Table of the bins with ≥ 50% completeness

MetaT Analysis

Overarching analysis - changes in metagenome content over time

COG accumulation over time

Is time a factor that affects the functional richness of phylosphere communities (Alpha Diversity)?

Do we see changes over time in functional richness?

Is there a difference between treatment (Fertilized vs. Unfertilized)?

Is there a difference between host plant?

PCoA

Is there similarity between the WGS communities and the 16S data (mantel/procrustes)?

How variable are metagenomes across replicate time points?

Metatranscriptomic Sequencing

MetaT Sequencing and Alignment Summaries

What is the abundance and quality of the reads in each sample?

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How do the reads align to the Switchgrass assembly?

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How do the reads align to the MAG assembly?

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About MultiQC

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